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Application and Development of EEG Acquisition and Feedback Technology: A Review

This review focuses on electroencephalogram (EEG) acquisition and feedback technology and its core elements, including the composition and principles of the acquisition devices, a wide range of applications, and commonly used EEG signal classification algorithms. First, we describe the construction...

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Detalles Bibliográficos
Autores principales: Qin, Yong, Zhang, Yanpeng, Zhang, Yan, Liu, Sheng, Guo, Xiaogang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10605290/
https://www.ncbi.nlm.nih.gov/pubmed/37887123
http://dx.doi.org/10.3390/bios13100930
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author Qin, Yong
Zhang, Yanpeng
Zhang, Yan
Liu, Sheng
Guo, Xiaogang
author_facet Qin, Yong
Zhang, Yanpeng
Zhang, Yan
Liu, Sheng
Guo, Xiaogang
author_sort Qin, Yong
collection PubMed
description This review focuses on electroencephalogram (EEG) acquisition and feedback technology and its core elements, including the composition and principles of the acquisition devices, a wide range of applications, and commonly used EEG signal classification algorithms. First, we describe the construction of EEG acquisition and feedback devices encompassing EEG electrodes, signal processing, and control and feedback systems, which collaborate to measure faint EEG signals from the scalp, convert them into interpretable data, and accomplish practical applications using control feedback systems. Subsequently, we examine the diverse applications of EEG acquisition and feedback across various domains. In the medical field, EEG signals are employed for epilepsy diagnosis, brain injury monitoring, and sleep disorder research. EEG acquisition has revealed associations between brain functionality, cognition, and emotions, providing essential insights for psychologists and neuroscientists. Brain–computer interface technology utilizes EEG signals for human–computer interaction, driving innovation in the medical, engineering, and rehabilitation domains. Finally, we introduce commonly used EEG signal classification algorithms. These classification tasks can identify different cognitive states, emotional states, brain disorders, and brain–computer interface control and promote further development and application of EEG technology. In conclusion, EEG acquisition technology can deepen the understanding of EEG signals while simultaneously promoting developments across multiple domains, such as medicine, science, and engineering.
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spelling pubmed-106052902023-10-28 Application and Development of EEG Acquisition and Feedback Technology: A Review Qin, Yong Zhang, Yanpeng Zhang, Yan Liu, Sheng Guo, Xiaogang Biosensors (Basel) Review This review focuses on electroencephalogram (EEG) acquisition and feedback technology and its core elements, including the composition and principles of the acquisition devices, a wide range of applications, and commonly used EEG signal classification algorithms. First, we describe the construction of EEG acquisition and feedback devices encompassing EEG electrodes, signal processing, and control and feedback systems, which collaborate to measure faint EEG signals from the scalp, convert them into interpretable data, and accomplish practical applications using control feedback systems. Subsequently, we examine the diverse applications of EEG acquisition and feedback across various domains. In the medical field, EEG signals are employed for epilepsy diagnosis, brain injury monitoring, and sleep disorder research. EEG acquisition has revealed associations between brain functionality, cognition, and emotions, providing essential insights for psychologists and neuroscientists. Brain–computer interface technology utilizes EEG signals for human–computer interaction, driving innovation in the medical, engineering, and rehabilitation domains. Finally, we introduce commonly used EEG signal classification algorithms. These classification tasks can identify different cognitive states, emotional states, brain disorders, and brain–computer interface control and promote further development and application of EEG technology. In conclusion, EEG acquisition technology can deepen the understanding of EEG signals while simultaneously promoting developments across multiple domains, such as medicine, science, and engineering. MDPI 2023-10-17 /pmc/articles/PMC10605290/ /pubmed/37887123 http://dx.doi.org/10.3390/bios13100930 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Qin, Yong
Zhang, Yanpeng
Zhang, Yan
Liu, Sheng
Guo, Xiaogang
Application and Development of EEG Acquisition and Feedback Technology: A Review
title Application and Development of EEG Acquisition and Feedback Technology: A Review
title_full Application and Development of EEG Acquisition and Feedback Technology: A Review
title_fullStr Application and Development of EEG Acquisition and Feedback Technology: A Review
title_full_unstemmed Application and Development of EEG Acquisition and Feedback Technology: A Review
title_short Application and Development of EEG Acquisition and Feedback Technology: A Review
title_sort application and development of eeg acquisition and feedback technology: a review
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10605290/
https://www.ncbi.nlm.nih.gov/pubmed/37887123
http://dx.doi.org/10.3390/bios13100930
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